March 2024 arXiv papers — page 134

Oshando Johnson, Goran Piskachev, Ranjith Krishnamurthy, Eric Bodden

To detect security vulnerabilities, static analysis tools need to be configured with security-relevant methods. Current approaches can automatically identify such methods using binary relevance machine learning approaches. However, they ignore dependencies among security-relevant methods, over-generalize and perform poorly in practice. Additionally, users ha

Likun Li, Haoqi Zeng, Changpeng Yang, Haozhe Jia

The objective of personalization and stylization in text-to-image is to instruct a pre-trained diffusion model to analyze new concepts introduced by users and incorporate them into expected styles. Recently, parameter-efficient fine-tuning (PEFT) approaches have been widely adopted to address this task and have greatly propelled the development of this field

Wen-Fei Wang, Li-Fei Yang, Ai-Jun Ma, Àngels Ramos

Very recently, the Belle~II Collaboration presented a measurement for the decays $B^+\to\bar{D}^{(*)0} K^+\bar{K}^0$ and $B^0\to D^{(*)-}K^+\bar{K}^0$, the bulk of observed $m(K^+ K_S^0)$ distributions showing low-mass structures in all four channels. In this work, we study the contributions of $\rho(770,1450)^+$, $a_2(1320)^+$ and $a_0(980,1450)^+$ resonanc

Priyanka Jalan, Vikram Khaire, M. Vivek, Prakash Gaikwad

We introduce FLAME, a machine-learning algorithm designed to fit Voigt profiles to HI Lyman-alpha (Ly$\alpha$) absorption lines using deep convolutional neural networks. FLAME integrates two algorithms: the first determines the number of components required to fit Ly$\alpha$ absorption lines, and the second calculates the Doppler parameter $b$, the HI column

Yuan Lian

In this article, we introduce the concepts of Weyl mean equicontinuity and Weyl mean sensitivity of a random dynamical system associated to an infinite countable discrete amenable group action. We obtain the dichotomy result to Weyl mean equicontinuity and Weyl mean sensitivity of a random dynamical system when the corresponding skew product transformation i

Nirmal Raj, Prajwal Shivanna, Gaurav Niraj Rachh

Neutron stars cooling passively since their birth may be reheated in their late-stage evolution by a number of possible phenomena: rotochemical, vortex creep, crust cracking, magnetic field decay, or more exotic processes such as removal of neutrons from their Fermi seas (the nucleon Auger effect), baryon number-violating nucleon decay, and accretion of part

Jimmy Huy Tran, Tore Selland Kleppe

Three approaches for adaptively tuning diagonal scale matrices for HMC are discussed and compared. The common practice of scaling according to estimated marginal standard deviations is taken as a benchmark. Scaling according to the mean log-target gradient (ISG), and a scaling method targeting that the frequency of when the underlying Hamiltonian dynamics cr

Siting Zhu, Renjie Qin, Guangming Wang, Jiuming Liu

We propose SemGauss-SLAM, a dense semantic SLAM system utilizing 3D Gaussian representation, that enables accurate 3D semantic mapping, robust camera tracking, and high-quality rendering simultaneously. In this system, we incorporate semantic feature embedding into 3D Gaussian representation, which effectively encodes semantic information within the spatial

Fernando Diaz-Diaz, Ernesto Estrada

Signed graphs are an emergent way of representing data in a variety of contexts where antagonistic interactions exist. These include data from biological, ecological, and social systems. Here we propose the concept of communicability for signed graphs and explore in depth its mathematical properties. We also prove that the communicability induces a hypersphe

Peichen Xie

Suppose $x$ is an approximation of $y$. This paper proposes using $\frac{|x-y|}{1+|y|}$, named Hyb Error, to measure the error. This metric equals half the harmonic mean of absolute error and relative error, effectively combining their advantages while mitigating their limitations. For example, Hyb Error approaches absolute error as $|y|$ approaches 0, there

Markus Zajac, Uta Störl

Quantum computers promise polynomial or exponential speed-up in solving certain problems compared to classical computers. However, in practical use, there are currently a number of fundamental technical challenges. One of them concerns the loading of data into quantum computers, since they cannot access common databases. In this vision paper, we develop a hy

Kaissar Nabbout, Martin Sommerfeld

In this work, some of the parameters influencing the cooling capacity of a liquid jet impinging onto Inconel 718 and C45 plates were experimentally investigated. The experiment included a high-speed camera to record the dynamic of the jet during the cooling process while an infrared camera was used to record the temperature field at the opposite surface. Jet

Kevin Iván Piterman

We show that the $p$-group complex of a finite group $G$ is homotopy equivalent to a wedge of spheres of dimension at most $n$ if $G$ contains a self-centralising normal subgroup $H$ which is isomorphic to a group of Lie type and Lie rank $n$ in characteristic $p$. If in addition every order-$p$ element of $G$ induces an inner or field automorphism on $H$, t

Yuan Lian

In this article, I give a definition of topological entropy for random dynamical systems associated to an infinite countable discrete amenable group action. I obtain a variational principle between the topological entropy and measurable fiber entropy of a random dynamical system.

Zeyu Zhang, Akide Liu, Ian Reid, Richard Hartley

Human motion generation stands as a significant pursuit in generative computer vision, while achieving long-sequence and efficient motion generation remains challenging. Recent advancements in state space models (SSMs), notably Mamba, have showcased considerable promise in long sequence modeling with an efficient hardware-aware design, which appears to be a

Morine Delhelle, Ingrid Van Keilegom

In this paper we consider a time-to-event variable $T$ that is subject to random right censoring, and we assume that the censoring time $C$ is stochastically dependent on $T$ and that there is a positive probability of not observing the event. There are various situations in practice where this happens, and appropriate models and methods need to be considere

Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon

In recent years, Explainable AI (XAI) methods have facilitated profound validation and knowledge extraction from ML models. While extensively studied for classification, few XAI solutions have addressed the challenges specific to regression models. In regression, explanations need to be precisely formulated to address specific user queries (e.g.\ distinguish

Janina Schreiber, Pau Batlle, Damar Wicaksono, Michael Hecht

We introduce a surrogate-based black-box optimization method, termed Polynomial-model-based optimization (PMBO). The algorithm alternates polynomial approximation with Bayesian optimization steps, using Gaussian processes to model the error between the objective and its polynomial fit. We describe the algorithmic design of PMBO and compare the results of the

Tomasz Żuchowski

For a free filter $F$ on $\omega$, let $N_F=\omega\cup\{p_F\}$, where $p_F\not\in\omega$, be equipped with the following topology: every element of $\omega$ is isolated whereas all open neighborhoods of $p_F$ are of the form $A\cup\{p_F\}$ for $A\in F$. The aim of this paper is to study spaces of the form $N_F$ in the context of the Nikodym property of Boole

Zeyu Zhang, Khandaker Asif Ahmed, Md Rakibul Hasan, Tom Gedeon

Diabetes, resulting from inadequate insulin production or utilization, causes extensive harm to the body. Existing diagnostic methods are often invasive and come with drawbacks, such as cost constraints. Although there are machine learning models like Classwise k Nearest Neighbor (CkNN) and General Regression Neural Network (GRNN), they struggle with imbalan

Ido Efrat

The mod-2 arithmetic Milnor invariants, introduced by Morishita, provide a decomposition law for primes in canonical Galois extensions of $\mathbb{Q}$ with unitriangular Galois groups, and contain the Legendre and Redei symbols as special cases. Morishita further proposed a notion of mod-q arithmetic Milnor invariants, where q is a prime power, for number fi

Douglas Newman

The seven binary quantum numbers that distinguish fundamental fermions have been shown to be conserved in decays and interactions. Here applications of this law are clarified to take account of odd (uct) and even (dsb) parity quarks defining separate representations of SU(3), each with its own definition of the F and G quantum numbers that distinguish genera

Oliver Robert Fox, Giacomo Bergami

This seminal paper proposes a new query language for graph matching and rewriting overcoming {the declarative} limitation of Cypher while outperforming {Neo4j} on graph matching and rewriting by at least one order of magnitude. We exploited columnar databases (KnoBAB) to represent graphs using the Generalised Semistructured Model.

Johannes Kellendonk

The Ellis semigroup of a dynamical system $(X,T)$ is tame if every element is the limit of a sequence (as opposed to a net) of homeomorphisms coming from the $T$ action. This topological property is related to the cardinality of the semigroup. Non-tame Ellis semigroups have a cardinality which is that of the power set of the continuum $2^{\mathfrak c}$.The s

Muhammad Sajjad, Andrea Russo, Maite Arcos, Andrzej Grudka

We study a quantum oscillator interacting and back-reacting on a classical oscillator. This can be done consistently provided the quantum system decoheres, while the backreaction has a stochastic component which causes the classical system to undergo diffusion. Nonetheless the state of the quantum oscillator can remain pure conditioned on the trajectory of t

Andreas Damianou, Francesco Fabbri, Paul Gigioli, Marco De Nadai

In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions. In this regard, two of the biggest trends in research around this subject are Graph Neural Networks (GNNs) and Foundation Models (FMs). While GNNs emerged

Błażej Żmija

Let $M=(m_{i})_{i=0}^{\infty}$ be a sequence of integers such that $m_{0}=1$ and $m_{i}\geq 2$ for $i\geq 1$. In this paper we study $M$-ary partition polynomials $(p_{M}(n,t))_{n=0}^{\infty}$ defined as the coefficient in the following power series expansion: \begin{align*} \prod_{i=0}^{\infty}\frac{1}{1-tq^{M_{i}}} = \sum_{n=0}^{\infty} p_{M}(n,t)q^{n}, \e

Pan Ting, Jianfeng Lin, Wenhao Yu, Wenlong Zhang

Object counting is a challenging task with broad application prospects in security surveillance, traffic management, and disease diagnosis. Existing object counting methods face a tri-fold challenge: achieving superior performance, maintaining high generalizability, and minimizing annotation costs. We develop a novel training-free class-agnostic object count

Netan Dogra

We give refined methods for proving finiteness of the Chabauty--Coleman--Kim set $X(\mathbb{Q}_2 )_2 $, when $X$ is a hyperelliptic curve with a rational Weierstrass point. The main developments are methods for computing Selmer conditions at $2$ and $\infty$ for the mod 2 Bloch--Kato Selmer group associated to the higher Chow group $\mathrm{CH}^2 (\mathrm{Ja

Zhiheng Lyu, Jiannan Yang, Zhongzhi Xu, Weilan Wang

We develop a deep learning model, ABioSPATH, to predict the one-year risk of ischemic stroke (IS) in atrial fibrillation (AF) patients. The model integrates drug-protein-disease pathways and real-world clinical data of AF patients to generate the IS risk and potential pathways for each patient. The model uses a multilayer network to identify the mechanism of

Jules Mercadier, Yaya Doumbia, Stefan Bittner, Marc Sciamanna

We experimentally study the synchronization of chaos generated by semiconductor lasers in a cascade injection configuration, i.e., a tunable master laser is used to generate chaos by optical injection in a transmitter laser that injects light into a receiver laser. Chaos synchronization between the transmitter and the receiver lasers is achieved with a corre

Gaston Mendoza Veirana, Philippe De Smedt, Jeroen Verhegge, Wim Cornelis

This study introduces Pedophysics, an open-source Python package designed to facilitate solutions for users who work in the field of soil assessment using near-surface geophysical electromagnetic techniques. At the core of this software is the ability to translate geophysical data into specific soil properties (and vice-versa) using pedophysical models (PM).

Robin Zbinden, Nina van Tiel, Marc Rußwurm, Devis Tuia

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting environmental conditions to species occurrences. Traditionally limited by a scarcity of species observations, these models have significantly improved in performance through the int

Lucas de Lara, Mathis Deronzier, Alberto González-Sanz, Virgile Foy

The push-forward operation enables one to redistribute a probability measure through a deterministic map. It plays a key role in statistics and optimization: many learning problems (notably from optimal transport, generative modeling, and algorithmic fairness) include constraints or penalties framed as push-forward conditions on the model. However, the liter

Yuanfei Lin, Chenran Li, Mingyu Ding, Masayoshi Tomizuka

Motion planners are essential for the safe operation of automated vehicles across various scenarios. However, no motion planning algorithm has achieved perfection in the literature, and improving its performance is often time-consuming and labor-intensive. To tackle the aforementioned issues, we present DrPlanner, the first framework designed to automaticall

Ting Yu, Xiaojun Lin, Shuhui Wang, Weiguo Sheng

Three-Dimensional (3D) dense captioning is an emerging vision-language bridging task that aims to generate multiple detailed and accurate descriptions for 3D scenes. It presents significant potential and challenges due to its closer representation of the real world compared to 2D visual captioning, as well as complexities in data collection and processing of

Yan-Qing Zhao, Xin-Li Sheng, Si-Wen Li, Defu Hou

We study the mass spectra and spin alignment of vector meson $J/\psi$ in a thermal magnetized background using a generalized theoretical framework based on gauge/gravity duality. Utilizing a soft wall model for the QGP background and a massive vector field for the $J/\psi$ meson, we delve into the meson's spectral function and spin parameters $(\lambda_{\the

Ivan Novikov

We study $\lambda$-discounted zero-sum games as the discount factor $\lambda$ approaches $0$ (that is, the players are more and more patient), in the context of games with stage duration. In stochastic games with stage duration $h$, players act at times $0, h, 2h$, and so on. The payoff and leaving probabilities are proportional to $h$. When $h$ tends to $0$

Stefan Kindermann, Simon Hubmer

We consider different norms for the Radon transform $Rf$ of a function $f$ and investigate under which conditions they can be estimated from above or below by some standard norms for $f$. We define Fourier-based norms for $Rf$ which can be related to Bessel-potential space norms for $f$. Furthermore, we define a variant of a total-variation norm for $Rf$ and

Marco Chilese, Richard Mitev, Meni Orenbach, Robert Thorburn

Control-Flow Attestation (CFA) is a security service that allows an entity (verifier) to verify the integrity of code execution on a remote computer system (prover). Existing CFA schemes suffer from impractical assumptions, such as requiring access to the prover's internal state (e.g., memory or code), the complete Control-Flow Graph (CFG) of the prover's so

Myrto Limnios, Stéphan Clémençon

In this paper we develop a novel nonparametric framework to test the independence of two random variables $\mathbf{X}$ and $\mathbf{Y}$ with unknown respective marginals $H(dx)$ and $G(dy)$ and joint distribution $F(dx dy)$, based on {\it Receiver Operating Characteristic} (ROC) analysis and bipartite ranking. The rationale behind our approach relies on the

Hongwei Zhang, Xiaoyin Xu, Dongsheng An, Xianfeng Gu

Backdoor attacks become a significant security concern for deep neural networks in recent years. An image classification model can be compromised if malicious backdoors are injected into it. This corruption will cause the model to function normally on clean images but predict a specific target label when triggers are present. Previous research can be categor

Dmitrii Dobrynin, Lorenzo Cardarelli, Markus Müller, Alejandro Bermudez

Characterizing the dynamics of quantum systems is a central task for the development of quantum information processors (QIPs). It serves to benchmark different devices, learn about their specific noise, and plan the next hardware upgrades. However, this task is also very challenging, for it requires a large number of measurements and time-consuming classical

Felix Rörentrop, Samira Boddin, Dorothee Knees, Jörn Mosler

The modeling of cracks is an important topic - both in engineering as well as in mathematics. Since crack propagation is characterized by a free boundary value problem (the geometry of the crack is not known beforehand, but part of the solution), approximations of the underlying sharp-interface problem based on phase-field models are often considered. Focusi

Camila Fernandez, Chung Shue Chen, Chen Pierre Gaillard, Alonso Silva

Time-to-event analysis is a branch of statistics that has increased in popularity during the last decades due to its many application fields, such as predictive maintenance, customer churn prediction and population lifetime estimation. In this paper, we review and compare the performance of several prediction models for time-to-event analysis. These consist

Xiang Li, Jin Liu, Tao Liu

A unique feature of non-Hermitian systems is the extreme sensitivity of the eigenspectrum to boundary conditions with the emergence of the non-Hermitian skin effect (NHSE). A NHSE originates from the point-gap topology of complex eigenspectrum, where an extensive number of eigenstates are anomalously localized at the boundary driven by nonreciprocal dissipat

Francesco Salzano, Simone Scalabrino, Rocco Oliveto, Remo Pareschi

Smart Contracts are programs running logic in the Blockchain network by executing operations through immutable transactions. The Blockchain network validates such transactions, storing them into sequential blocks of which integrity is ensured. Smart Contracts deal with value stakes, if a damaging transaction is validated, it may never be reverted, leading to

Sergiy Borodachov, Peter Boyvalenkov, Peter Dragnev, Douglas Hardin

Universal bounds for the potential energy of weighted spherical codes are obtained by linear programming. The universality is in the sense of Cohn-Kumar -- every attaining code is optimal with respect to a large class of potential functions (absolutely monotone), in the sense of Levenshtein -- there is a bound for every weighted code, and in the sense of par

Ana Lawry Aguila, Andre Altmann

There has been a growing interest in recent years in modelling multiple modalities (or views) of data to for example, understand the relationship between modalities or to generate missing data. Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to tailor thei

Philipp Sikorski, Alec G. R. Thomas, Stepan S. Bulanov, Matt Zepf

In this article we investigate novel signatures of radiation reaction via the angular deflection of an electron beam colliding at 90 degrees with an intense laser pulse. Due to the radiation reaction effect, the electrons can be deflected towards the beam axis for plane wave backgrounds, which is not possible in the absence of radiation reaction effects. The

Henrik Häggström, Pedro L. C. Rodrigues, Geoffroy Oudoumanessah, Florence Forbes

Bayesian inference for complex models with an intractable likelihood can be tackled using algorithms performing many calls to computer simulators. These approaches are collectively known as "simulation-based inference" (SBI). Recent SBI methods have made use of neural networks (NN) to provide approximate, yet expressive constructs for the unavailable likelih

Erich Novak, Friedrich Pillichshammer

The $L_p$-discrepancy is a classical quantitative measure for the irregularity of distribution of an $N$-element point set in the $d$-dimensional unit cube. Its inverse for dimension $d$ and error threshold $\varepsilon \in (0,1)$ is the number of points in $[0,1)^d$ that is required such that the minimal normalized $L_p$-discrepancy is less or equal $\varep

Jiali Wang, Yang Tang, Luca Schenato

Given the widespread attention to individual thermal comfort, coupled with significant energy-saving potential inherent in energy management systems for optimizing indoor environments, this paper aims to introduce advanced "Humans-in-the-building" control techniques to redefine the paradigm of indoor temperature design. Firstly, we innovatively redefine the

Jan O. Schunck, Jens Buck, Robin Y. Engel, Simon R. Kruse

The detection of inelastically scattered soft X-rays with high energy resolution usually requires large grating spectrometers. Recently, photoelectron spectrometry for analysis of X-rays (PAX) has been rediscovered for modern spectroscopy experiments at synchrotron light sources. By converting scattered photons to electrons and using an electron energy analy

Sam Adriaensen, Robin Simoens, Leo Storme

We characterise the minimum weight codewords of the $p$-ary linear code of intersecting lines in ${\rm PG}(3,q)$, $q=p^h$, $q\geq19$, $p$ prime, $h\geq 1$. If $q$ is even, the minimum weight equals $q^3+q^2+q+1$. If $q$ is odd, the minimum weight equals $q^3+2q^2+q+1$. For $q$ even, we also characterise the codewords of second smallest weight.

Fernanda Famá, Charalampos Kalalas, Sandra Lagen, Paolo Dini

In multiple federated learning schemes, a random subset of clients sends in each round their model updates to the server for aggregation. Although this client selection strategy aims to reduce communication overhead, it remains energy and computationally inefficient, especially when considering resource-constrained devices as clients. This is because convent

David Florez, Hubert Piquet, Eric Bru, Rafael Diez

This work presents a simple power converter, without any high voltage transformer, able to supply and control a plasma jet based on dielectric barrier discharge. The converter, operating in pulsed current mode, requires a single power switch and is fed by a low voltage DC source. It can deliver very short duration pulses to the plasma jet with high current a

X. Ding, Y. Fan, X. X. Wang, C. H. Li

The superconducting infinite-layer (IL) nickelates offer a new platform for investigating the long-standing problem of high-temperature superconductivity. Many models were proposed to understand its superconducting mechanisms based on the calculated electronic structure, and the multiple Fermi surfaces and multiple orbitals involved create complications and

Jannes Nys, Gabriel Pescia, Alessandro Sinibaldi, Giuseppe Carleo

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational challenge. Our work introduces a variational approach for fermionic time-dependent wave functions, surpassing mean-field a

Daniel West, Susan Stepney, Y. Hancock

Prostate cancer is a disease which poses an interesting clinical question: should it be treated? A small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients, hence, new methods of approach to biomolecularly subclassify the

Julian Pick, Roman Schwarz, Jens Kruse, Christian Lisdat

Today's best optical lattice clocks are based on the spectroscopy of trapped alkaline-earth-like atoms such as ytterbium and strontium atoms. The development towards mobile or even space-borne clocks necessitates concepts for the compact laser-cooling and trapping of these atoms with reduced laser requirements. Here we present two compact and robust achromat

Jiawei Cheng

In this paper, we study the fourth-order Schr\"{o}dinger equation \begin{equation*} i \partial_t u + {\Delta}^2 u - \gamma \Delta u = \pm |u|^{s-1}u \end{equation*} on the lattice $\mathbb{Z}^d$ with dimensions $d=1,2$ and parameter $\gamma \in \mathbb{R}$. In order to establish sharp dispersive estimates, we consider the fundamental solution as an oscillato

Rongqing Zhang, Hanqiu Wang, Bing Li, Xiang Cheng

The development of Intelligent Transportation System (ITS) has brought about comprehensive urban traffic information that not only provides convenience to urban residents in their daily lives but also enhances the efficiency of urban road usage, leading to a more harmonious and sustainable urban life. Typical scenarios in ITS mainly include traffic flow pred

Yoshiro Kakehashi

Magnetic phase diagram for the Hubbard model on the Beta-Mn type lattice has been calculated as a function of the Coulomb interaction energy parameter U and the electron number per atom n by using the generalized Hartree-Fock approximation combined with the recursion method for electronic-structure calculations. The ferromagnetic state, the ferrimagnetic sta

Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou

We study the problem of domain adaptation under distribution shift, where the shift is due to a change in the distribution of an unobserved, latent variable that confounds both the covariates and the labels. In this setting, neither the covariate shift nor the label shift assumptions apply. Our approach to adaptation employs proximal causal learning, a techn

Shujun Zhao, Hao-jie Xu, You Zhou, Yu-Xin Liu

The shape phase transition for certain isotope or isotone chains, associated with the quantum phase transition of finite nuclei, is an intriguing phenomenon in nuclear physics. A notable case is the Xe isotope chain, where the structure transits from a $\gamma$-soft rotor to a spherical vibrator, with the second-order shape phase transition occurring in the

Yao Liang, Yuwei Wang, Yang Li, Yi Zeng

Fine-tuning techniques based on Large Pretrained Language Models (LPLMs) have been proven to significantly enhance model performance on a variety of downstream tasks and effectively control the output behaviors of LPLMs. Recent studies have proposed numerous methods for fine-tuning a small number of parameters based on open-source LPLMs, reducing the demand

Quentin Cormier

We study a renewal problem within a periodic environment, departing from the classical renewal theory by relaxing the assumption of independent and identically distributed inter-arrival times. Instead, the conditional distribution of the next arrival time, given the current one, is governed by a periodic kernel, denoted as $H$. The periodicity property of $H

Arati Bhattu, Svenja Hermann, Nidhal Jamia, Florian Müller

The Tribomechadynamics Research Challenge (TRC) was a blind prediction of the vibration behavior of a thin plate clamped on two sides using bolted joints. The first bending mode's natural frequency and damping ratio were requested as function of the amplitude, starting from the linear regime until high levels, where both frictional contact and nonlinear bend

Bowen Liu, Wei Liu, Siang Chen, Pengwei Xie

The goal of object pose estimation is to visually determine the pose of a specific object in the RGB-D input. Unfortunately, when faced with new categories, both instance-based and category-based methods are unable to deal with unseen objects of unseen categories, which is a challenge for pose estimation. To address this issue, this paper proposes a method t

Hanyu Zhou, Zhiwei Shi, Hao Dong, Shihan Peng

Event-based moving object detection is a challenging task, where static background and moving object are mixed together. Typically, existing methods mainly align the background events to the same spatial coordinate system via motion compensation to distinguish the moving object. However, they neglect the potential spatial tailing effect of moving object even

Weiting Lin, Yuchieh Wu, Borching Su

Satellite communications (SatComs) are anticipated to deliver global Internet access. Low Earth orbit (LEO) satellites (SATs) offer the advantage of higher downlink capacity due to their reduced link budget compared to medium Earth orbit (MEO) and geostationary Earth orbit (GEO) SATs. In this paper, beam broadening methods for uniform rectangular arrays (URA

Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska

We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for automated tumor segmentation. The practicality of current learning-based automated tissue classification approaches is severely impeded by their dependency on manually segmented tra

Zebin Qiu, Muneto Nitta

We propose a novel baryonic vortex phase in low energy dense QCD with finite baryon and isospin chemical potentials. It is known that the homogeneous charged pion condensate emerges as a ground state at finite isospin chemical potential, and therein arises the Abrikosov vortex lattice with an applied magnetic field. We first demonstrate that a vortex with th

Hanyu Zhou, Yi Chang, Zhiwei Shi, Luxin Yan

Single RGB or LiDAR is the mainstream sensor for the challenging scene flow, which relies heavily on visual features to match motion features. Compared with single modality, existing methods adopt a fusion strategy to directly fuse the cross-modal complementary knowledge in motion space. However, these direct fusion methods may suffer the modality gap due to

Zeyu Li, Kangxiang Qin, Yong He, Wang Zhou

Transfer learning has aroused great interest in the statistical community. In this article, we focus on knowledge transfer for unsupervised learning tasks in contrast to the supervised learning tasks in the literature. Given the transferable source populations, we propose a two-step transfer learning algorithm to extract useful information from multiple sour

Marc Winstel

In this work, we demonstrate that the mixing of scalar and vector condensates produces spatially oscillating, but exponentially damped correlation functions in fermionic theories at finite density and temperature. We find a regime exhibiting this oscillatory behavior in a Gross-Neveu-type model that also features vector interactions within the mean-field app

Teng Long, Jiahuan Ren, Peng Li, Feng Yun

The polarization control of micro/nano lasers is an important topic in nanophotonics. Up to now, the simultaneous generation of two distinguishable orthogonally-polarized lasing modes from a single organic microlaser remains a critical challenge. Here, we demonstrate simultaneously orthogonally-polarized dual lasing from a microcavity filled with an organic

Davide Manfredo, Vanessa Dörlich, Joachim Linn, Martin Arnold

The present work aims at describing hysteresis behaviour arising from cyclic bending experiments on cables by means of the Preisach operator. Pure bending experiments conducted in previous work show that slender structures such as electric cables behave inelastically and open hysteresis loops arise, with noticeable difference between the first load cycle and

Michael Götz, Christian Weber, Christoph Kolb, Klaus Maier-Hein

In machine learning larger databases are usually associated with higher classification accuracy due to better generalization. This generalization may lead to non-optimal classifiers in some medical applications with highly variable expressions of pathologies. This paper presents a method for learning from a large training base by adaptively selecting optimal

Uri Malamud

Although there is abundant and diverse observational evidence in support of white dwarf stars hosting planets or debris disks which form in the catastrophic destruction of various planetary bodies, the key processes that explain these observations are still being intensely investigated. The study of white dwarf planetary systems offers a unique perspective o

A. Alexandre, L. Anderson, T. Collin-Dufresne, T. Guérin

We consider the motion of a harmonically trapped overdamped particle, which is submitted to a self-phoretic force, that is proportional to the gradient of a diffusive field for which the particle itself is the source. In agreement with existing results for free particles or particles in a bounded domain, we find that the system exhibits a transition between

Raphael Stuhlmeier, Conor Heffernan, Alberto Alberello, Emilian Părău

This paper sets out to explore the modulational (or Benjamin-Feir) instability of a monochromatic wave propagating in the presence of damping such as that induced by sea-ice on the ocean surface. The fundamental wave motion is modelled using the spatial Zakharov equation, to which either uniform or non-uniform (frequency dependent) damping is added. By means

Adam Lesnikowski, Valentin T. Bickel, Daniel Angerhausen

The NASA Lunar Reconnaissance Orbiter (LRO) has returned petabytes of lunar high spatial resolution surface imagery over the past decade, impractical for humans to fully review manually. Here we develop an automated method using a deep generative visual model that rapidly retrieves scientifically interesting examples of LRO surface imagery representing the f

Rasoul Samani, Mohammad Dehghani, Fahime Shahrokh

Hospital readmission, defined as patients being re-hospitalized shortly after discharge, is a critical concern as it impacts patient outcomes and healthcare costs. Identifying patients at risk of readmission allows for timely interventions, reducing re-hospitalization rates and overall treatment costs. This study focuses on predicting patient readmission wit

Hao-Ting Pai, Yu-Hsuan Kang, Wen-Cheng Chung

Recent advancements in Intrusion Detection Systems (IDS), integrating Explainable AI (XAI) methodologies, have led to notable improvements in system performance via precise feature selection. However, a thorough understanding of cyber-attacks requires inherently explainable decision-making processes within IDS. In this paper, we present the Interpretable Gen

Florian Müller, Malte Krack

A beam-slider system is considered whose passive self-adaption relies on an intricate locomotion process involving both frictional and unilateral contact. The system also exploits geometric nonlinearity to achieve broadband efficacy. The dynamics of the system take place on three distinct time scales: On the fast time scale of the harmonic base excitation ar

Yuchuan Wu, Zhenyong Hou, Wenxian Li, Xianyong Bai

Upflows and downflows at active region (AR) boundaries have been frequently observed with spectroscopic observations at extreme ultraviolet (EUV) passbands. In this paper, we report the coexistence of upflows and downflows at the AR boundaries with imaging observations from the Solar Upper Transition Region Imager (SUTRI) and the Atmospheric Imaging Assembly

Katsuhisa Koshino

Given a metrizable space $X$, let $AM(X)$ be the space of continuous bounded admissible metrics on $X$, which is endowed with the sup-metric. In this paper, we shall investigate the Borel complexity and the complete metrizability of $AM(X)$ and show that a separable metrizable space $X$ is $\sigma$-compact if and only if $AM(X)$ is completely metrizable.

Jian Zhang, Changlin Yang, Haiping Zhu, Qika Lin

Document-level Event Argument Extraction (DEAE) aims to identify arguments and their specific roles from an unstructured document. The advanced approaches on DEAE utilize prompt-based methods to guide pre-trained language models (PLMs) in extracting arguments from input documents. They mainly concentrate on establishing relations between triggers and entity

Weijia Wu, Zhuang Li, Yuchao Gu, Rui Zhao

We introduce DragAnything, which utilizes a entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control methods, DragAnything offers several advantages. Firstly, trajectory-based is more userfriendly for interaction, when acquiring other guidance signals (e.g., masks, depth maps) is l

Roy Elkayam, Ovadia Lev

Means to increase water resources are essential in regions grappling with water scarcity and growing populations. Soil aquifer treatment (SAT) is a cheap, low maintenance, low-energy method to supply water for irrigation of crops consumed raw or even for drinking purposes. However, the most expensive cost-component of SATs is the land use, the infiltration b

Shu-Qing Li, Wen-Jing Xing, Shanshan Cao, Guang-You Qin

Heavy flavor particles provide important probes of the microscopic structure and thermodynamic properties of the quark-gluon plasma (QGP) produced in high-energy nucleus-nucleus collisions. We study the energy loss and flow of charm and bottom quarks inside the QGP via the nuclear modification factor ($R_\mathrm{AA}$) and elliptic flow coefficient ($v_2$) of

Elia Bisi, Fabio Deelan Cunden

We consider random matrices whose shape is the dilation $N\lambda$ of a self-conjugate Young diagram $\lambda$. In the large-$N$ limit, the empirical distribution of the squared singular values converges almost surely to a probability distribution $F^{\lambda}$. The moments of $F^{\lambda}$ enumerate two combinatorial objects: $\lambda$-plane trees and $\lam

Pingwei Sun

Accurately handling the underlying support values in sentences is crucial for understanding the speaker's tendencies, yet it poses a challenging task in natural language understanding (NLU). In this article, we explore the potential of fine-tuning and prompt tuning in this downstream task, using the Human Value Detection 2023. Additionally, we attempt to val

Ming Yang, Dongkai Zhang, Lixiang Chen

Recent advancements have expanded Hardy's nonlocality arguments into multisetting and multidimensional systems to enhance quantum correlations. In comparison with Hardy's nonlocal argument, Cabello's nonlocal argument (CNA) emerges as a superior choice for illustrating nonlocal features. An open question persists regarding the potential extension of CNA to a

A. K. Boukellal, M. Sarebanzadeh, A. Orozco-Caballero, F. Sket

Grain growth competition during directional solidification of a polycrystal with hexagonal (hcp) symmetry (Mg-1wt%Gd alloy) is studied by phase-field modeling, exploring the effect of the temperature gradient G on the resulting grain boundary (GB) orientation selection. Results show that selection mechanisms and scaling laws derived for cubic (fcc, bcc) crys

T. Chaumont-Frelet, S. Nicaise

We consider time-harmonic elastodynamic problems in heterogeneous media.cWe focus on scattering problems in the high-frequency regime and incnearly incompressible media, where the the angular frequency $\omega$ and ratio of the Lam\'e parameters $\lambda/\mu$ may both be large. We derive stability estimates controlling the norm of the solution by the norm of

Vitaly Shalumov, Harel Haskey, Yuval Solaz

In this paper, we introduce summarization MevakerSumm and conclusion extraction MevakerConc datasets for the Hebrew language based on the State Comptroller and Ombudsman of Israel reports, along with two auxiliary datasets. We accompany these datasets with models for conclusion extraction (HeConE, HeConEspc) and conclusion allocation (HeCross). All of the co

Shiying Lu, Emanuele Daddi, Claudia Maraston, Mark Dickinson

Dating the ages and weighting the stellar populations in galaxies are essential steps when studying galaxy formation through cosmic times. Evolutionary population synthesis models with different input physics are used for this purpose. Moreover, the contribution from the thermally pulsing asymptotic giant branch (TP-AGB) stellar phase, which peaks for interm